Recently, societal trends have indicated that a sizable portion of the population have been and will continue to suffer from sleep deprivation. Although much research has been performed on the causes of and potential remedies for sleep deprivation, research into the effects of sleep deprivation on the cognitive performance of an individual has been relatively more limited.
Much of the research into the effect of sleep loss on cognitive effectiveness has been directed towards algorithmic techniques for correlating sleep and wake states with cognitive effectiveness levels. U.S. Pat. No. 6,241,686 (hereinafter “Balkin”) entitled “System and Method for Predicting Human Cognitive Performance Using Data from an Actigraph” and U.S. Pat. No. 6,579,233 (hereinafter “Hursh”) entitled “System and Method for Evaluating Task Effectiveness Based on Sleep Pattern” each propose algorithmic techniques for correlating sleep loss with cognitive effectiveness and making past or future predictions of cognitive performance based, generally, on measured sleep and wake states and are fully incorporated by reference herein.
In addition to the algorithmic techniques, these and other references propose systems for measuring the sleep and wake states of an individual, performing analysis of this measured data and presenting the results to a user. However, these approaches lack the capability to adapt sufficiently to variations between individual users, fail to present data to users in a fully comprehensive manner, and suffer from inefficient data collection and analysis techniques.
Accordingly, improved devices, systems and methods for monitoring and evaluating individual performance are needed.